Daiying Zhao

Debiasing the Fine-Grained Classification Task in LLMs with Bias-Aware PEFT

Fine-grained classification via LLMs is susceptible to more complex label biases compared to traditional classification tasks. Existing bias mitigation strategies, such as retraining, post-hoc adjustment, and parameter-efficient fine-tuning (PEFT) are primarily effective for simple classification bi…